The present disclosure relates generally to the use of the combined visible and near infra red spectrum in an apparatus and method for measuring physical parameters, e.g., firmness, density and internal and external disorders, and chemical parameters, e.g., molecules containing Oxe2x80x94H, Nxe2x80x94H and Cxe2x80x94H chemical bonds, in fruit and correlating the resulting measurements with fruit quality and maturity characteristics, including Brix, acidity, density, pH, firmness, color and internal and external defects to forecast consumer preferences including taste preferences and appearance, as well as harvest, storage and shipping variables. With the present apparatus and method, the interior of a sample, e.g., fruit including apples, is illuminated and the spectrum of absorbed and scattered light from the sample is detected and measured. Prediction, calibration and classification algorithms are determined for the category of sample permitting correlation between the spectrum of absorbed and scattered light and sample characteristics, e.g., fruit quality and maturity characteristics.
The embodiments disclosed herein has a focus on combined visible and near-infrared (NIR) spectroscopy and its modes of use, major issues in the application of NIR to the measurement of Oxe2x80x94H, Nxe2x80x94H and Cxe2x80x94H containing molecules that are indicators of sample quality including fruit quality and in particular tree fruit quality.
Near-Infrared Spectroscopy Background: Near-infrared spectroscopy has been used since the 1970""s for the compositional analysis of low moisture food products. However, only in the last 10-15 years has NIR been successfully applied to the analysis of high moisture products such as fruit. NIR is a form of vibrational spectroscopy that is particularly sensitive to the presence of molecules containing Cxe2x80x94H (carbon-hydrogen), Oxe2x80x94H (oxygen-hydrogen), and Nxe2x80x94H (nitrogen-hydrogen) groups. Therefore, constituents such as sugars and starch (Cxe2x80x94H), moisture, alcohols and acids (Oxe2x80x94H), and protein (Nxe2x80x94H) can be quantified in liquids, solids and slurries. In addition, the analysis of gases (e.g., water vapor, ammonia) is possible. NIR is not a trace analysis technique and it is generally used for measuring components that are present at concentrations greater than 0.1%.
Short-Wavelength NIR vs. Long-Wavelength NIR: NIR has traditionally been carried out in the 1100-2500 nm region of the electromagnetic spectrum. However, the wavelength region of xcx9c700-1100 nm (short wavelength-NIR or SW-NIR) has been gaining increased attention. The SW-NIR region offers numerous advantages for on-line and in-situ bulk constituent analysis. This portion of the NIR is accessible to low-cost, high performance silicon detectors and fiber optics. In addition, high intensity laser diodes and low-cost light emitting diodes are becoming increasingly available at a variety of NIR wavelength outputs.
The relatively low extinction (light absorption) coefficients in the SW-NIR region yields linear absorbance with analyte concentration and permits long, convenient pathlengths to be used. The depth of penetration of SW-NIR is also much greater than that of the longer wavelength NIR, permitting a more adequate sampling of the xe2x80x9cbulkxe2x80x9d material. This is of particular importance when the sample to be analyzed is heterogeneous such as fruit.
Diffuse Reflectance Sampling vs. Transmission Sampling: Traditional NIR analysis has used diffuse reflectance sampling. This mode of sampling is convenient for samples that are highly light scattering or samples for which there is no physical ability to employ transmission spectroscopy. Diffusely reflected light is light that has entered a sample, undergone multiple scattering events, and emerged from the surface in random directions. A portion of light that enters the sample is also absorbed. The depth of penetration of the light is highly dependent on the sample characteristics and is often affected by the size of particles in the sample and the sample density. Furthermore, diffuse reflectance is biased to the surface of a sample and may not provide representative data for large heterogeneous samples such as apples.
While transmission sampling is typically used for the analysis of clear solutions, it also can be used for interrogating solid samples. A transmission measurement is usually performed with the detector directly opposite the light source (i.e., at 180 degrees) and with the sample in the center. Alternately the detector can be placed closer to the light source (at angles less than 180 degrees), which is often necessary to provide a more easily detected level of light. Because of the long sample pathlengths and highly light scattering nature of most tree fruit, transmission measurements can only be performed in the SW-NIR wavelength region, unless special procedures are employed to improve signal to noise.
NIR Calibration: NIR analysis is largely an empirical method; the spectral lines are difficult to assign, and the spectroscopy is frequently carried out on highly light scattering samples where adherence to Beer""s Law is not expected. Accordingly, statistical calibration techniques are often used to determine if there is a relationship between analyte concentration (or sample property) and instrument response. To uncover this relationship requires a representative set of xe2x80x9ctrainingxe2x80x9d or calibration samples. These samples must span the complete range of chemical and physical properties of all future samples to be seen by the instrument.
Calibration begins by acquiring a spectrum of each of the samples. Constituent values for all of the analytes of interest are then obtained using the best reference method available with regards to accuracy and precision. It is important to note that a quantitative spectral method developed using statistical correlation techniques can perform no better than the reference method.
After the data has been acquired, computer models employing statistical calibration techniques are developed that relate the NIR spectra to the measured constituent values or properties. These calibration models can be expanded and must be periodically updated and verified using conventional testing procedures.
Factors affecting calibration include fruit type and variety, seasonal and geographical differences, and whether the fruit is fresh or has been in cold or other storage. Calibration variables include the particular properties or analytes to be measured and the concentration or level of the properties. Intercorrelations (co-linearity) should be minimized in calibration samples so as not to lead to false interpretation of a models predictive ability. Co-linearity occurs when the concentrations of two components are correlated, e.g., an inverse correlation exists when one component is high, the other is always low or vice versa.
Application of NIR to Tree Fruit and Existing On-Line NIR Instrumentation: A growing body of research exists for NIR analysis of tree fruit. NIR has been used for the measurement of fruit juice, flesh, and whole fruit. In juice, the individual sugars (sucrose, fructose, glucose) and total acidity can be quantified with high correlation ( greater than 0.95) and acceptable error. Individual sugars can not be readily measured in whole fruit. Brix is the most successfully measured NIR parameter in whole fruit and can generally be achieved with an error of xc2x10.5-1.0 Brix. More tentative recent research results indicate firmness and acidity measurement in whole fruit also may be possible.
Only in Japan has the large-scale deployment of on-line NIR for fruit sorting occurred. These instruments require manual placement/orientation of the fruit prior to measurement and early versions were limited to a measurement rate of three samples per second. The Japanese NIR instruments are also limited to a single lane of fruit and appear to be difficult to adapt to multi-lane sorting equipment used in the United States of America. While earlier Japanese NIR instruments employed reflectance sampling, more recent instruments use transmission sampling.
In Koashi et al., U.S. Pat. No. 4,883,953, there is described a method and apparatus for measuring sugar concentrations in liquids. Measurements are made at two different depths using weak and strong infrared radiation. The level of sugar at depths between these two depths can then be measured. The method and apparatus utilizes wavelength bands of 950-1,150 nm, 1,150-1,300 nm, and 1,300-1,450 nm.
U.S. Pat. No. 5,089,701, to Dull et al., uses near infrared (NIR) radiation in the wavelength range of 800-1,050 nm to demonstrate measurement of soluble solids in Honeydew melons. An eight-centimeter or greater distance between the light delivery location to the fruit and the light collection location was found to be necessary to accurately predict soluble solids because of the thick rind.
Iwamoto et al., U.S. Pat. No. 5,324,945, also use NIR radiation to predict sugar content of mandarin oranges. Iwamoto utilizes a transmission measurement arrangement whereby the light traverses through the entire sample of fruit and is detected at 180 degrees relative to the light input angle. Moderately thick-skinned fruit (mandarin oranges) were used to demonstrate the method, which relies on a fruit diameter correction by normalizing (dividing) the spectra at 844 nm, where, according to the disclosed data, correlation with the sugar content is lowest. NIR wavelengths in the range of 914-919 nm were found to have the highest correlation with sugar content. Second, third and fourth wavelengths that were added to the multiple regression analysis equation used to correlate the NIR spectra with sugar content were 769-770 nm, 745 nm, and 785-786 nm.
In U.S. Pat. No. 5,708,271, Ito et al. demonstrates a sugar content measuring apparatus that utilizes three different NIR wavelengths in the range from 860-960 nm. The angle between fight delivery and collection was varied between 0 and 180 degrees and it was concluded that the low NIR radiation levels that must be detected when a photo-detector is placed at 180 degrees relative to the radiation source are not desirable because of the more complicated procedures and equipment that are required. A correlation of NIR absorbance with sugar content of muskmelons and watermelons was found when an intermediate angle, which gave greater NIR radiation intensity, was detected. No size correction was necessary with this approach.
U.S. Pat. No. 4,883,953 to Koashi et al. uses comparatively long wavelengths of NIR radiation (i.e.,  greater than 950 nm), while in U.S. Pat. No. 5,089,701 to Dull, and U.S. Pat. No. 5,708,271 to Ito, wavelengths of NIR radiation used are greater than 800 nm and 860 nm, respectively. In U.S. Pat. No. 5,324,945 to Iwamoto, the wavelengths of NIR radiation with the highest correlation to sugar content of mandarins were 914 nm or 919 nm, when the fruit were measured on the equatorial or stem portion, respectively.
All of these methods use near-infrared wavelengths of light to correlate with sugar content of whole fruit. No other quality parameters are measured by these techniques.
The four disclosed patents are similar to the apparatus and method described here in that the present disclosure also measures sugar content. Two of the patents (U.S. Pat. Nos. 5,089,701 and 5,324,945) NIR wavelengths less than 850 nm) U.S. Pat. No. 5,089,701 discloses the operation of the invention within the range of xe2x80x9cfrom about 800 nanometers to about 1050 nanometers.xe2x80x9d U.S. Pat. No. 5,324,945 lists 914 nm or 919 nm as the primary analytical wavelength correlated with whole fruit sugar content; multiple linear regression was used to add successive wavelengths to the model as follows: 769-770 nm (2nd wavelength added), 745 nm (3rd wavelength added), and 785-786 nm (4th wavelength added). In U.S. Pat. No. 5,089,701, addition of the fourth wavelength to the model only reduced the standard error of prediction (SEP) by 0.1-0.2 Brix, which is approaching or less than the error limits of the refractometer used to determine the reference (xe2x80x9ctruexe2x80x9d) Brix values.
Other similarities between the method and apparatus described herein with the four patents listed above include the use of multivariate statistical analysis to establish correlation of the near-infrared spectral data with sugar content of whole fruit. Most also use data processing techniques such as second derivative transformation and some type of spectral normalization. All of these methods for relating NIR spectra to chemical or physical properties are well known to those practiced in the art of NIR spectroscopy.
The foregoing patents and printed publications are provided herewith in an Information Disclosure Statement in accordance with 37 CFR 1.97.
Research groups around the world continue to explore the applications of near infrared spectroscopy to tree fruit. The apparatus and process disclosed herein is of the nondestructive determination or prediction of Oxe2x80x94H, Nxe2x80x94H and Cxe2x80x94H containing molecules that are indicators of sample qualities, including fruit such as apples, cherries, oranges, grapes, potatoes, cereals, and other such samples, using near infrared spectroscopy. Prior art has utilized spectrum from 745 nm and above. This disclosure is of 1) the utilization of the spectrum from 250 nm to 1150 nm for measurement or prediction of one or more parameters, e.g., Brix, firmness, acidity, density, pH, color and external and internal defects and disorders including, for example, surface and subsurface bruises, scarring, sun scald, punctures, watercore, internal browning, in samples including fruit; 2) an apparatus and method of illuminating the interior of a sample and detecting emitted light from samples exposed to the above spectrum in at least one spectrum range and, in the preferred embodiment, in at least two spectrum ranges of 250 to 499 nm and 500 nm to 1150 nm; 3) the use of the chlorophyl absorption band, pealing at 680 nm, in combination with the spectrum from 700 nm and above to predict one or more of the above parameters; 4) the use of the visible pigment region, including xanthophyll, from approximately 250 nm to 499 nm and anthocyanin from approximately 500 to 550 nm, in combination with the chlorophyl band and the spectrum from 700 nm and above to predict the all of the above parameters.
Prior art has only examined spectrum from fruit for the prediction of Brix. This disclosure is of the examination of a greater spectrum using the combined visible and near infrared wavelength regions for the prediction of the above stated characteristics. The apparatus and method disclosed eliminates the problem of saturation of light spectrum detectors within particular spectrum regions while gaining data within other regions in the examination, in particular, of fruit. That is, spectrometers with CCD (charge coupled device) array or PDA (photodiode array) detectors will detect light within the 250 to 1150 nm region, but when detecting spectrum out of fruit will saturate in regions, e.g., 700 to 925 nm, or the signal to noise (S/N) ratio will be unsatisfactory and not useful for quantitation in other regions, e.g., 250 to 699 nm and greater than 925 nm, thus precluding the gaining of additional information regarding the parameters above stated. Thus disclosed herein is an apparatus and method permitting 1) the automated measurement of multiple spectra with a single pass or single measurement activity by detecting more than one spectrum range during a single pass or single measurement activity, 2) combining the more than one spectrum range detected, 3) comparing the combined spectrum with a stored calibration algorithm to 4) predicting the parameters above stated.
In each instance in the method and apparatus disclosed herein there will be a dual or plural spectrum acquisition from a sample from different spectrum regions. This is accomplished by 1) serially acquiring data from different spectrum regions using different light source intensities or different detector/spectrometer exposure times using a single spectrometer; 2) acquiring data in parallel with multiple spectrometers using different light intensities, e.g., by varying the voltage input to a lamp, or different exposure times to the spectrometers; however, different exposure times leads to sampling errors particularly where a sample is moving, e.g., in a processing line, due to viewing different regions on a sample; and 3) with multiple spectrometers using the same exposure time, constant lamp intensity with dual or a plurality of light detectors including neutral density filtered light detectors (where filtered light detectors giving the same effect as using a shorter exposure time). This approach provides dual or plural spectra with good signal to noise ratio for all wavelengths intensities using a single light source intensity and the same exposure time on all spectrometer detectors. This approach uses at least one filtered light detector using filtered input 82 to the spectrometer 170 rather than different exposure times. A filter can be any material that absorbs light with equal strength over the range of wavelengths used by the spectrometer including but not limited to neutral density filters, Spectralon, Teflon, opal coated glass, screen. The dual intensity approach using two different lamp voltages proves problematic because the high and low intensity spectra are not easily combined together due to slope differences in the spectra. The dual exposure approach yields excellent combined spectra, which are necessary for firmness and other characteristic prediction and also improves Brix prediction accuracy.
Measurements are disclosed, with the apparatus and process of this disclosure, which are made simultaneously in multiple sample types, e.g., where samples are apples, measurement is independent of a particular apple cultivar, using a single calibration equation with errors of xc2x11-2 lb. and xc2x10.5-1.0 Brix. This disclosure pertains to laboratory, portable and on-line NIR analyzers for the simultaneous measurement of multiple quality parameters of samples including fruit. Depending on the application or particular characteristic sought to be predicted or measured, a variety of calibration models may be used, from universal to highly specific, e.g., the calibration can be specific to a variety, different geographical location, stored v. fresh fruit and other calibrations.
Disclosed here is the greater role NIR technology will play as a tool for grading sample qualities including fruit quality. The unique ability of NIR statistical calibration techniques to extract non-chemical xe2x80x9cpropertiesxe2x80x9d provides a technique for development of a general NIR xe2x80x9cquality indexxe2x80x9d for tree fruit. This general xe2x80x9cquality indexxe2x80x9d combines all of the information that could be extracted from the NIR spectra and includes information about Brix, acidity, firmness, density, pH, color and external and internal disorders and defects.
The near-infrared wavelength region below 745 nm has not been explored by prior investigations. Generally, the prior art design and or apparatus utilized was such that longer wavelength regions provided adequate data. The prior art for measuring sugar content in liquids and whole fruits using near-infrared spectroscopy utilizes longer wavelengths of radiation. No prior art exists for measuring other important quality parameters such as firmness, acidity, density and pH. No prior art has correlated consumer taste preferences with the combined NIR determination of multiple quality parameters such as sugar, acidity, pH, firmness, color, and internal and external defects and disorders.
It will be shown in this patent that the wavelength region from 250-1150 nm can be used to nondestructively measure not only sugar content (Brix) in various whole fruit, but firmness, density, acidity, pH, color and internal and external defects as well. For example, density of oranges is measured and is correlated to quality, e.g., freeze damaged fruit and dry fruit typically have lower density than good quality fruit and lower water content (i.e., greater dry matter content). NIR density measurement can be used to remove poor quality fruit in a sorting/packing line or at the supermarket. Information about color pigments and chlorophyll, related to maturity and quality, are obtained from 250 to approximately 699 nm. From approximately 700-1150 nm, the shortwavelength NIR region, Cxe2x80x94H, Nxe2x80x94H, Oxe2x80x94H information is obtained. Combining the visible and NIR region gives more analytical power to predict chemical, physical and consumer properties, particularly for fruit. All of these parameters can be determined simultaneously from a combined visible/NIR spectrum. Multiple parameters can be combined to arrive at a xe2x80x9cQuality Indexxe2x80x9d that is a better measure of maturity or quality than a single parameter.
Absorption of light by whole fruit in the approximately 250-699 nm region is dominated by pigments, including chlorophyll (a green pigment) which absorbs in the approximately 600-699 nm region. Chlorophyll is composed of a number of chlorophyll-protein complexes. Changes in these chlorophyll-protein complexes and changes in other pigments, most notably anthocyanin (red pigment) and xanthophylls (yellow pigments), are related to the maturation and ripening process. Chlorophyll and pigments are important for determining firmness.
While the NIR wavelengths of 700-925 nm and longer have been readily accessible to common near-infrared spectrometers, shorter wavelengths have not typically been explored for the following reasons: 1) lead-salt and other detector types, e.g., InGaAs, were not sensitive to shorter wavelengths; 2) light diffraction gratings were blazed at longer wavelengths yielding poor efficiency at short wavelengths; 3) light sources did not have enough energy output at shorter wavelengths to overcome the strong light absorption and scattering of biological (plant and animal) material in the visible region (250-699 nm).
Disclosed herein is an apparatus and method for measurement, with the visible/near-infrared (VIS/NIR) spectroscopic technique for sugar content (also known as Brix or soluble solids, which is inversely related to dry matter content), firmness, acidity, density, pH, color and internal and external defects and disorders. The apparatus and method is successful in measuring one or more such characteristic in apples, grapes, oranges, potatoes and cherries. Demonstrated in this disclosure is the ability to combine chemical and physical property data permitting the prediction of consumer properties, such as taste, appearance and color; harvest variables, such as time for harvest; and storage variables such as prediction of firmness retention and time until spoilage.